SQL
1 Introduction to SQL
1.1 Overview of SQL
1.2 History and Evolution of SQL
1.3 Importance of SQL in Data Management
2 SQL Basics
2.1 SQL Syntax and Structure
2.2 Data Types in SQL
2.3 SQL Statements: SELECT, INSERT, UPDATE, DELETE
2.4 SQL Clauses: WHERE, ORDER BY, GROUP BY, HAVING
3 Working with Databases
3.1 Creating and Managing Databases
3.2 Database Design Principles
3.3 Normalization in Database Design
3.4 Denormalization for Performance
4 Tables and Relationships
4.1 Creating and Modifying Tables
4.2 Primary and Foreign Keys
4.3 Relationships: One-to-One, One-to-Many, Many-to-Many
4.4 Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
5 Advanced SQL Queries
5.1 Subqueries and Nested Queries
5.2 Common Table Expressions (CTEs)
5.3 Window Functions
5.4 Pivoting and Unpivoting Data
6 Data Manipulation and Aggregation
6.1 Aggregate Functions: SUM, COUNT, AVG, MIN, MAX
6.2 Grouping and Filtering Aggregated Data
6.3 Handling NULL Values
6.4 Working with Dates and Times
7 Indexing and Performance Optimization
7.1 Introduction to Indexes
7.2 Types of Indexes: Clustered, Non-Clustered, Composite
7.3 Indexing Strategies for Performance
7.4 Query Optimization Techniques
8 Transactions and Concurrency
8.1 Introduction to Transactions
8.2 ACID Properties
8.3 Transaction Isolation Levels
8.4 Handling Deadlocks and Concurrency Issues
9 Stored Procedures and Functions
9.1 Creating and Executing Stored Procedures
9.2 User-Defined Functions
9.3 Control Structures in Stored Procedures
9.4 Error Handling in Stored Procedures
10 Triggers and Events
10.1 Introduction to Triggers
10.2 Types of Triggers: BEFORE, AFTER, INSTEAD OF
10.3 Creating and Managing Triggers
10.4 Event Scheduling in SQL
11 Views and Materialized Views
11.1 Creating and Managing Views
11.2 Uses and Benefits of Views
11.3 Materialized Views and Their Use Cases
11.4 Updating and Refreshing Views
12 Security and Access Control
12.1 User Authentication and Authorization
12.2 Role-Based Access Control
12.3 Granting and Revoking Privileges
12.4 Securing Sensitive Data
13 SQL Best Practices and Standards
13.1 Writing Efficient SQL Queries
13.2 Naming Conventions and Standards
13.3 Documentation and Code Comments
13.4 Version Control for SQL Scripts
14 SQL in Real-World Applications
14.1 Integrating SQL with Programming Languages
14.2 SQL in Data Warehousing
14.3 SQL in Big Data Environments
14.4 SQL in Cloud Databases
15 Exam Preparation
15.1 Overview of the Exam Structure
15.2 Sample Questions and Practice Tests
15.3 Time Management Strategies
15.4 Review and Revision Techniques
Database Design Principles

Database Design Principles

1. Normalization

Normalization is the process of organizing the data in a database to reduce redundancy and improve data integrity. It involves dividing larger tables into smaller, more manageable tables and defining relationships between them. The most common forms of normalization are First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF).

Example:

CREATE TABLE Customers (
    CustomerID INT PRIMARY KEY,
    Name VARCHAR(100),
    Address VARCHAR(255)
);

CREATE TABLE Orders (
    OrderID INT PRIMARY KEY,
    CustomerID INT,
    OrderDate DATE,
    FOREIGN KEY (CustomerID) REFERENCES Customers(CustomerID)
);
    

In this example, the Customers and Orders tables are normalized. The CustomerID in the Orders table is a foreign key that references the CustomerID in the Customers table, ensuring data integrity and reducing redundancy.

2. Entity-Relationship (ER) Modeling

Entity-Relationship (ER) modeling is a graphical approach to database design. It involves identifying entities (objects or concepts) and their relationships within a system. ER diagrams help in visualizing the structure of a database and understanding how different entities interact with each other.

Example:

Consider a university database with entities like Students, Courses, and Professors. The ER diagram would show that a Student can enroll in multiple Courses, and a Course can be taught by multiple Professors. This visual representation helps in designing the database schema effectively.

3. Indexing

Indexing is a technique used to improve the speed of data retrieval operations on a database table. An index is a data structure that stores a sorted list of the contents of a specified column, allowing the database to find data more quickly. Proper indexing can significantly enhance query performance.

Example:

CREATE INDEX idx_customer_name
ON Customers (Name);
    

In this example, an index named idx_customer_name is created on the Name column of the Customers table. This index will speed up queries that filter or sort by the Name column.